зеркало из https://github.com/mozilla/bugbug.git
114 строки
3.5 KiB
Python
114 строки
3.5 KiB
Python
# -*- coding: utf-8 -*-
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# This Source Code Form is subject to the terms of the Mozilla Public
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# License, v. 2.0. If a copy of the MPL was not distributed with this file,
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# You can obtain one at http://mozilla.org/MPL/2.0/.
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import argparse
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import csv
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import json
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import os
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import sys
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from datetime import date, datetime, timedelta
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# Inject project path
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sys.path.append("../")
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def fetch_untriaged(args):
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from bugbug import bugzilla
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today = date.today()
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three_months_ago = today - timedelta(days=args.days_back)
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# Set bugzilla token and download bugs
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bugzilla.set_token(args.token)
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bug_ids = bugzilla.get_ids_between(three_months_ago, today)
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bugs = bugzilla.get(bug_ids)
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# Get untriaged bugs
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untriaged_bugs = []
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for bug in bugs.values():
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for history in bug["history"]:
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for change in history["changes"]:
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if (
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change["field_name"] == "component"
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and change["removed"] == "Untriaged"
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):
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untriaged_bugs.append(bug)
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with open("bugs-{}.json".format(datetime.now().strftime("%s")), "w") as f:
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json.dump(untriaged_bugs, f)
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return untriaged_bugs
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def run_untriaged(untriaged_bugs):
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from bugbug.models.component import ComponentModel
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from bugbug.models.component_nn import ComponentNNModel
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models = [
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(ComponentModel, "../componentmodel"),
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(ComponentNNModel, "../componentnnmodel"),
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]
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for (model_class, model_file_name) in models:
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rows = []
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model = model_class.load(model_file_name)
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for bug in untriaged_bugs:
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p = model.classify(bug, probabilities=True)
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url = f'https://bugzilla.mozilla.org/show_bug.cgi?id={bug["id"]}'
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classifiable = p[p >= 0.7].size >= 1
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classification = ""
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expected_component = model.filter_component(
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bug["product"], bug["component"]
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)
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if not expected_component:
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print("Skipping bug: {}".format(bug["id"]))
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continue
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if classifiable:
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print("Classifying bug with ID: {}".format(bug["id"]))
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classification = model.classify(bug)[0]
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print("Classified bug as: {}".format(classification))
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else:
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print("Not classifiable bug: {}".format(bug["id"]))
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correct_prediction = expected_component == classification
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rows.append(
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[
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url,
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classifiable,
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expected_component,
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classification,
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correct_prediction,
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bug["summary"],
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]
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)
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os.makedirs("sheets", exist_ok=True)
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class_name = model.__class__.__name__
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timestamp = datetime.utcnow().strftime("%Y-%m-%d")
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sheet_name = f"{class_name}-{timestamp}-labels.csv"
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with open(os.path.join("sheets", sheet_name), "w") as f:
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writer = csv.writer(f)
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writer.writerows(rows)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--token", help="Bugzilla API token")
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parser.add_argument("--days-back", type=int, help="Days since to fetch bugs")
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parser.add_argument("--file_path", help="Days since to fetch bugs")
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args = parser.parse_args()
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if args.file_path:
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with open(args.file_path, "r") as f:
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bugs = json.load(f)
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else:
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bugs = fetch_untriaged(args)
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run_untriaged(bugs)
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